AI Engineer

Airbus
Bengaluru
Workplace: OnsiteFull timeFunction: Data Science & Machine LearningExperience: 4-7 yearsEducation: bachelorsSkills: ["Strategic product mindset","Communication","Innovative problem-solving","User advocacy"]

Build and deploy production-grade AI/ML products that automate complex engineering workflows and accelerate software transformation. Own end-to-end AI product lifecycle from architecture and fine-tuning through monitoring and performance optimization. Create NLP/LLM and RAG-driven solutions to parse and modernize legacy codebases and documentation, leveraging GCP (Vertex AI, Cloud Run, BigQuery, GKE). Drive engineering excellence with CI/CD, testing, and FinOps cost optimization.

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FursaFursa
Airbus
Airbus
1 day ago

AI Engineer

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Source: Company careers pageValidated by: Fursa AI
Last checked: 1 hour agoStatus: Live

Job Summary

Build and deploy production-grade AI/ML products that automate complex engineering workflows and accelerate software transformation. Own end-to-end AI product lifecycle from architecture and fine-tuning through monitoring and performance optimization. Create NLP/LLM and RAG-driven solutions to parse and modernize legacy codebases and documentation, leveraging GCP (Vertex AI, Cloud Run, BigQuery, GKE). Drive engineering excellence with CI/CD, testing, and FinOps cost optimization.
Location: Bengaluru
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Lead the full lifecycle of advanced AI products, including architecture, model selection/fine-tuning, production deployment, monitoring, and performance optimization.
  • •Design NLP/LLM systems that parse, translate, and modernize legacy codebases and technical documentation.
  • •Build prompt architectures, RAG pipelines, and fine-tuned models to automate domain-specific artifact generation from user prompts.
  • •Implement scalable AI microservices and batch pipelines on GCP, using serverless and resilient architecture patterns.
  • •Establish AI engineering best practices with CI/CD, automated testing, robust API design, documentation, and FinOps cost tracking/optimization.

Key Requirements

  • •Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related quantitative field.
  • •4 to 7 years of hands-on experience building, deploying, and scaling end-to-end AI/ML products and generative AI applications.
  • •Must hold at least one recognized cloud or AI certification (e.g., Google Cloud Professional Machine Learning Engineer or equivalent).
  • •Strong ability to develop prompt architectures and RAG pipelines, including retrieval, fine-tuning, and automated domain-specific artifact generation.
  • •Experience leveraging Google Cloud Platform for production AI, including resilient serverless/scalable microservices and batch processing.
Experience:4-7 yearsAI/MLGenerative AIMLOpsCloudEnterprise software
Education:Bachelor's
Skills:Strategic product mindsetCommunicationInnovative problem-solvingUser advocacy
Certifications:Google Cloud Professional Machine Learning Engineer
Tech Stack:Google Cloud Platform (GCP)Vertex AICloud RunBigQueryCloud FunctionsGKELLMsNatural Language Processing (NLP)RAGRetrieval-augmented generationVector databasesPineconeChromaDBVertex Vector SearchLangChainLlamaIndexPythonREST APIsGRPCMicroservice design patterns

Company Brief

Airbus
Designs, manufactures, and sells commercial aircraft, helicopters, defense and space systems, and related services worldwide. Airbus is a leading aerospace and defense company delivering integrated solutions for civil and military aviation customers.
Industry: Aerospace Manufacturing
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Toulouse, France
Founded: 1970
WebsiteLinkedIn